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Recruitment AI Has a Disability Problem: Anticipating and Mitigating Unfair Automated Hiring Decisions

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Towards Trustworthy Artificial Intelligent Systems

Abstract

Artificial Intelligence (AI) technologies have the potential to dramatically impact the lives and life chances of people with disabilities seeking employment and throughout their career progression. While these systems are marketed as highly capable and objective tools for decision making, a growing body of research demonstrates a record of inaccurate results as well as inherent disadvantages for historically marginalised groups. Assessments of fairness in Recruitment AI for people with disabilities have thus far received little attention or have been overlooked. This paper examines the impacts to and concerns of disabled employment seekers using AI systems for recruitment, and discusses recommendations for the steps employers can take to ensure innovation in recruitment is also fair to all users. In doing so, we further the point that making systems fairer for disabled employment seekers ensures systems are fairer for all. disability, artificial intelligence, recruitment, human resources, hiring

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References

  1. Broussard M (2018) Artificial unintelligence: how computers misunderstand the world. MIT Press, Cambridge

    Book  Google Scholar 

  2. O’Neil C (2017) Weapons of math destruction: how big data increases inequality and threatens democracy. Penguin Random House, New York

    MATH  Google Scholar 

  3. Noble S (2018) Algorithms of oppression: how search engines reinforce racism. New York University Press, New York

    Book  Google Scholar 

  4. Guo A, Kamar E, Vaughan JW, Wallach H, Morris MR (2019) Toward fairness in AI for people with disabilities: a research roadmap. arXiv preprint arXiv:1907.02227

  5. Petrick ER (2015) Making computers accessible: disability rights and digital technology. Johns Hopkins University Press, Baltimore

    Google Scholar 

  6. Trewin S (2018) AI fairness for people with disabilities: point of view. arXiv preprint arXiv:1811.10670

  7. Trewin S, Basson S, Muller M, Branham S, Treviranus J, Gruen D, Hebert D, Lyckowski N, Manser E (2019) Considerations for AI fairness for people with disabilities. AI Matters 5(3):40–63

    Article  Google Scholar 

  8. Whittaker M, Alper M, Bennett CL, Hendren S, Kaziunas L, Mills M, West M (2019) Disability, bias, and AI. AI Now Institute, November

    Google Scholar 

  9. Collins PH, Bilge S (2020) Intersectionality. Wiley and Sons

    Google Scholar 

  10. Parker AM (2015) Intersecting histories of gender, race, and disability. J Women’s Hist 27:1

    Google Scholar 

  11. Samuels E (2016) Fantasies of identification: disability, gender. New York University Press, New York, Race

    Google Scholar 

  12. Frederick A, Shifrer D (2019) Race and disability: from analogy to intersectionality. Sociol Race Ethnicity 5(2):200–214

    Article  Google Scholar 

  13. Office for National Statistics, Disability and Employment, UK (2019). https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/disability/bulletins/disabilityandemploymentuk/2019

  14. Schur L (2002) The difference a job makes: the effects of employment among people with disabilities. J Econ Issues 36(2):339–347

    Article  Google Scholar 

  15. Sayce L (2011) Getting in, staying in and getting on: disability employment support fit for the future, vol 8081. The Stationery Office

    Google Scholar 

  16. Lindsay S, Leck J, Shen W, Cagliostro E, Stinson J (2019) A framework for developing employer’s disability confidence. Equal Divers Inclus Int J (2019)

    Google Scholar 

  17. Suter R, Scott-Parker S, Zadek S (2007) Realising potential: disability confidence builds better business. Employers’ Forum on Disability

    Google Scholar 

  18. Russell S, Norvig P (2003) Artificial intelligence: a modern approach, 2nd edn. Pearson Education

    Google Scholar 

  19. Davis L (2005) Disabilities in the workplace: recruitment, accommodation, and retention. AAOHN J 53(7):306–312

    Article  Google Scholar 

  20. Hamraie A (2017) Building access: universal design and the politics of disability. University of Minnesota Press, Minneapolis

    Book  Google Scholar 

  21. Følstad A, Brandtzæg PB, Feltwell T, Law EL, Tscheligi M, Luger EA (2018) SIG: chatbots for social good. In: Extended abstracts of the 2018 CHI conference on human factors in computing systems, pp 1–4

    Google Scholar 

  22. Edenborough R (2005) Assessment methods in recruitment, selection and performance: a manager’s guide to psychometric testing, interviews and assessment centres. Kogan Page Publishers

    Google Scholar 

  23. Smith K, Abrams SS (2019) Gamification and accessibility. Int J Inform Learn Technol

    Google Scholar 

  24. Cook DA, Beckman TJ (2006) Current concepts in validity and reliability for psychometric instruments: theory and application. Am J Med 119(2):166–167

    Article  Google Scholar 

  25. Leslie D (2020) Understanding bias in facial recognition technologies. arXiv preprint arXiv:2010.07023

Download references

Acknowledgements

We dedicate this chapter in the memory of James Partridge (Face Equality International) who contributed valuable insights to this research and whose advocacy transformed attitudes toward people with facial disfigurements. We appreciate the contributions and insights provided by Julien Burnett, Nigel Crook, Paul Jackson, and Rebecca Raper.

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Correspondence to Selin E. Nugent .

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Nugent, S.E., Scott-Parker, S. (2022). Recruitment AI Has a Disability Problem: Anticipating and Mitigating Unfair Automated Hiring Decisions. In: Ferreira, M.I.A., Tokhi, M.O. (eds) Towards Trustworthy Artificial Intelligent Systems. Intelligent Systems, Control and Automation: Science and Engineering, vol 102. Springer, Cham. https://doi.org/10.1007/978-3-031-09823-9_6

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